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Abstract Debris flows pose persistent hazards and shape high‐relief landscapes in diverse physiographic settings, but predicting the spatiotemporal occurrence of debris flows in postglacial topography remains challenging. To evaluate the debris flow process in high‐relief postglacial terrain, we conducted a geomorphic investigation to characterize geologic, glacial, volcanic, and land use contributions to landslide initiation across Southeast Alaska. To evaluate controls on landslide (esp. debris flow) occurrence in Sitka, we used field observation, geomorphic mapping, landslide characteristics as documented in the Tongass National Forest inventory, and a novel application of the shallow landslide model SHALSTAB to postglacial terrain. A complex geomorphic history of glaciation and volcanic activity provides a template for spatially heterogeneous landslide occurrence. Landslide density across the region is highly variable, but debris flow density is high on south‐ or southeast‐facing hillslopes where volcanic tephra soils are present and/or where timber harvest has occurred since 1900. High landslide density along the western coast of Baranof and Kruzof islands coincides with deposition of glacial sediment and thick tephra and exposure to extreme rainfall from atmospheric rivers on south‐facing aspects but the relative contributions of these controls are unclear. Timber harvest has also been identified as an important control on landslide occurrence in the region. Focusing on a subset of geo‐referenced landslides near Sitka, we used the SHALSTAB shallow landslide initiation model, which has been frequently applied in non‐glacial terrain, to identify areas of high landslide potential in steep, convergent terrain. In a validation against mapped landslide polygons, the model significantly outperformed random guessing, with area under the curve (AUC) = 0.709 on a performance classification curve of true positives vs. false positives. This successful application of SHALSTAB demonstrates practical utility for hazards analysis in postglacial landscapes to mitigate risk to people and infrastructure.
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A Community-Partnered Approach to Social Network Data Collection for a Large and Partial Network
In the small town of Sitka, Alaska, frequent and often catastrophic landslides threaten residents. One challenge associated with disaster preparedness is access to timely and reliable risk information. As with many small but diverse towns, who or what is a trustworthy source of information is often contested. To help improve landslide communication in Sitka, we used a community-partnered approach to social network analysis to identify (1) potential key actors for landslide risk communication and (2) structural holes that may inhibit efficient and equitable communication. This short take describes how we built trust and developed adaptive data collection methods to build an approach that was acceptable and actionable for Sitka, Alaska. This approach could be useful to other researchers for conducting social network analysis to improve risk communication, particularly in rural and remote contexts.
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- Award ID(s):
- 1831770
- PAR ID:
- 10362909
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Field Methods
- ISSN:
- 1525-822X
- Page Range / eLocation ID:
- Article No. 1525822X2210747
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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